Macroecological factors explain large-scale spatial population patterns of ancient agriculturalists

Aim: It has been well demonstrated that the large-scale distribution patterns of numerous species are driven by similar macroecological factors. However, understanding of this topic remains limited when applied to our own species. Here we take a large-scale look at ancient agriculturalist populations over the past two millennia. The main aim of this study was to test the hypothesis that the patterns of agriculturalist populations were shaped by relevant macroecological factors. Location: China. Methods: Using detailed historical census data, we reconstructed spatial patterns of human population density over 13 imperial dynasties in ancient China, which was dominated by agrarian societies. We used simultaneous autoregressive models to examine the population densities of agriculturalists in relation to climatic, topographic, edaphic and hydrological variables, together with the spatial structure of a concentration of population toward national capitals. The pure and shared effects of these variables and the population-concentration structure were decomposed using a variation partitioning procedure. Results: Spatial population patterns of ancient agriculturalists can be well modelled by climate, topography, soil properties and local hydrological systems. A plausible explanation is that by influencing crop yield these environmental factors essentially drive the distribution of agriculturalists. The population-concentration structure can also explain agriculturalist patterns to a considerable extent. This structure and those environmental factors have largely shared effects in simultaneously shaping these agriculturalist patterns. Main conclusions: While humans can effectively temper environmental constraints at small spatial scales, our results demonstrate that macroecological factors underpin the spatial patterns of humans at large scales. Macroecological constraints and their relative importance are found to be similar for humans and other species, suggesting that similar mechanisms are likely to underlie these macroecological patterns. Our findings have potential implications for the assessment of future responses of humans to global environmental changes.

[1]  Tatsuya Amano,et al.  Global distribution and drivers of language extinction risk , 2014, Proceedings of the Royal Society B: Biological Sciences.

[2]  James H Brown,et al.  Macroecology Meets Macroeconomics: Resource Scarcity and Global Sustainability. , 2014, Ecological engineering.

[3]  M. Lima.  Climate change and the population collapse during the “Great Famine” in pre-industrial Europe , 2014, Ecology and evolution.

[4]  William E. Banks,et al.  Ecological constraints on the first prehistoric farmers in Europe , 2013 .

[5]  S. Dray,et al.  Does local habitat fragmentation affect large‐scale distributions? The case of a specialist grassland bird , 2013 .

[6]  K. Cassman,et al.  Estimating crop yield potential at regional to national scales , 2013 .

[7]  Wenyun Zuo,et al.  The Macroecology of Sustainability , 2012, PLoS biology.

[8]  Kevin McGarigal,et al.  Estimating landscape resistance to movement: a review , 2012, Landscape Ecology.

[9]  James H Brown,et al.  Human macroecology: linking pattern and process in big‐picture human ecology , 2012, Biological reviews of the Cambridge Philosophical Society.

[10]  Bradford A. Hawkins,et al.  Eight (and a half) deadly sins of spatial analysis , 2012 .

[11]  J. Lobo,et al.  Using species distribution models in paleobiogeography: A matter of data, predictors and concepts , 2011 .

[12]  Kyle C. Meng,et al.  Civil conflicts are associated with the global climate , 2011, Nature.

[13]  Jed O. Kaplan,et al.  Holocene carbon emissions as a result of anthropogenic land cover change , 2011 .

[14]  B. McGill,et al.  Geographic disparities and moral hazards in the predicted impacts of climate change on human populations , 2011 .

[15]  Jane Zhang,et al.  Climate change and large-scale human population collapses in the pre-industrial era , 2011 .

[16]  Anette Reenberg,et al.  Complex Land Systems: the Need for Long Time Perspectives to Assess their Future , 2010 .

[17]  Navin Ramankutty,et al.  Mind the gap: how do climate and agricultural management explain the ‘yield gap’ of croplands around the world? , 2010 .

[18]  H. Lee,et al.  Changes in climate and secular population cycles in China, 1000 CE to 1911 , 2010 .

[19]  Jan Beck,et al.  Is the Spatial Distribution of Mankind's Most Basic Economic Traits Determined by Climate and Soil Alone? , 2010, PloS one.

[20]  D. Lobell,et al.  Warming increases the risk of civil war in Africa , 2009, Proceedings of the National Academy of Sciences.

[21]  H. Lee,et al.  Temperature, aridity thresholds, and population growth dynamics in China over the last millennium , 2009 .

[22]  N. Batjes,et al.  The Harmonized World Soil Database , 2009 .

[23]  J. Elith,et al.  Species Distribution Models: Ecological Explanation and Prediction Across Space and Time , 2009 .

[24]  William E. Banks,et al.  Neanderthal Extinction by Competitive Exclusion , 2008, PloS one.

[25]  Lincoln Fok,et al.  Climatic change and Chinese population growth dynamics over the last millennium , 2008 .

[26]  M. Araújo,et al.  The importance of biotic interactions for modelling species distributions under climate change , 2007 .

[27]  R. G. Davies,et al.  Methods to account for spatial autocorrelation in the analysis of species distributional data : a review , 2007 .

[28]  W. D. Kissling,et al.  Spatial autocorrelation and the selection of simultaneous autoregressive models , 2007 .

[29]  Carsten Rahbek,et al.  Food plant diversity as broad-scale determinant of avian frugivore richness , 2007, Proceedings of the Royal Society B: Biological Sciences.

[30]  Bruce T. Milne,et al.  Nonlinear scaling of space use in human hunter–gatherers , 2007, Proceedings of the National Academy of Sciences.

[31]  C. Field,et al.  Global scale climate–crop yield relationships and the impacts of recent warming , 2007, Environmental Research Letters.

[32]  Christina L. Tague,et al.  RHESSys: Regional Hydro-Ecologic Simulation System—An Object- Oriented Approach to Spatially Distributed Modeling of Carbon, Water, and Nutrient Cycling , 2004 .

[33]  Christopher Small,et al.  Global Population Distribution and Urban Land Use in Geophysical Parameter Space , 2004 .

[34]  M. Scheffer,et al.  Overexploitation of Renewable Resources by Ancient Societies and the Role of Sunk-Cost Effects , 2004 .

[35]  Richard Field,et al.  ENERGY, WATER, AND BROAD‐SCALE GEOGRAPHIC PATTERNS OF SPECIES RICHNESS , 2003 .

[36]  T. Dawson,et al.  Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? , 2003 .

[37]  Erik Matthysen,et al.  The application of 'least-cost' modelling as a functional landscape model , 2003 .

[38]  J. Diniz‐Filho,et al.  Spatial autocorrelation and red herrings in geographical ecology , 2003 .

[39]  M. Grosjean,et al.  Human Occupations and Climate Change in the Puna de Atacama, Chile , 2002, Science.

[40]  J. L. Macías,et al.  Sta. Cruz Atizapan: a 22-ka lake level record and climatic implications for the late Holocene human occupation in the Upper Lerma Basin, Central Mexico , 2002 .

[41]  Dawn M. Kaufman,et al.  THE GEOGRAPHIC RANGE: Size, Shape, Boundaries, and Internal Structure , 1996 .

[42]  D. Hodell,et al.  Possible role of climate in the collapse of Classic Maya civilization , 1995, Nature.

[43]  P. Legendre.  Spatial Autocorrelation: Trouble or New Paradigm? , 1993 .

[44]  James H. Brown.  On the Relationship between Abundance and Distribution of Species , 1984, The American Naturalist.

[45]  Rob Hengeveld,et al.  The distribution of abundance. I. Measurements , 1982 .

[46]  Kees Klein Goldewijk,et al.  The HYDE 3.1 spatially explicit database of human‐induced global land‐use change over the past 12,000 years , 2011 .

[47]  Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/joc.1276 VERY HIGH RESOLUTION INTERPOLATED CLIMATE SURFACES FOR GLOBAL LAND AREAS , 2005 .